What are the similarities and differences between data science and traditional data analytics

As far as data analysis is concerned, a solid understanding of mathematical and statistical skills is crucial, as well as programming skills and a working knowledge of online data visualization tools and intermediate statistics. Data analysts are well versed in SQL, they know some regular expressions and can slice and dice data. In the sciences, a thorough understanding of SQL databases and coding is required, in addition to a firm grasp of a large number of unstructured metrics and insights. Data scientists need more "sophisticated" skills in data modeling, predictive analytics, programming, data collection, and advanced statistics. Essentially, they need to have considerable machine learning and engineering or programming skills that allow them to manipulate data the way they want to.